The Control of the Cardiovascular System in Health and Disease

Wednesday, June 16 at 04:15am (PDT)
Wednesday, June 16 at 12:15pm (BST)
Wednesday, June 16 08:15pm (KST)

SMB2021 SMB2021 Follow Tuesday (Wednesday) during the "MS12" time block.
Note: this minisymposia has multiple sessions. The second session is MS11-NEUR (click here).

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Mette Olufsen (North Carolina State University, USA), Brian Carlson (University of Michigan, USA), Justen Geddes (North Carolina State University, USA)


The cardiovascular system delivers oxygen to all tissues in the body. The system is tightly controlled to supply oxygen under a diverse range of physiological conditions such as at rest, during postural changes, and exercise. Many studies have found that in a range of diseases, including COVID-19, cardiovascular function is compromised significantly impacting quality of life. The cardiovascular control system responds to mechanical, neural and hormonal stimuli and is difficult to study experimentally, as the system is best studied in the awake condition. Therefore, experimental measures e.g., heart rate, blood pressure, and respiration rate are typically non-invasive, and clinical invasive measures e.g., right heart catheterization, are only taken when the risk to the patient is minimal. A better understanding of how these non-invasive and low risk invasive measures can be used to quantitatively describe cardiovascular function is essential for improving diagnosis and treatment protocols. Numerous studies have used modeling to examine cardiovascular function and its control in animals and humans; however, more work is needed to translate these results to improve clinical protocols. This minisymposium focuses on exploring cardiovascular function - highlighting contributions that combine mathematical modeling, machine learning and signal processing.

Brian E. Carlson

(University of Michigan, Ann Arbor, MI, USA)
"Using Modeling to Understand Pathophysiology in the Cardiovascular Control System"
The state of the cardiovascular system can be assessed from time-series signals including heart rate and blood pressure. Characteristics of these signals are used to determine pathophysiology. Experienced clinicians can visually inspect signals and with high level of certainty determine key observed dynamics however analysis with computational models can uncover the underlying mechanisms driving these dynamics. This talk will address how mathematical modeling can be utilized to predict patient specific dynamics for patients with altered cardiovascular control system, including patients with heart failure and pulmonary hypertension. Focus will be on studying dynamics observed in response to an orthostatic challenge including the Valsalva maneuver and active standing. It is believed that through the analysis of these cardiovascular challenges a deeper level phenotyping of changes within the cardiovascular control system can be revealed. To understand how the system is impacted we use models to analyze patient specific changes observed during active standing, a Valsalva maneuver (breath holding), and deep breathing.

John S. Clemmer

(Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA)
"Physiological Modeling of Hypertensive Kidney Disease in African Americans"
Chronic kidney disease (CKD) is characterized by the progressive functional loss of nephrons and hypertension (HTN). Successful antihypertensive regimens attenuate the progression of CKD. While studies suggest that calcium channel blocker (CCB) therapy mitigates the decline in renal function in humans with essential HTN, there are few long-term clinical studies that determine the impact of CCBs in patients with hypertensive CKD. Dihydropyridine (DHP) or L-type CCBs preferentially vasodilate the afferent arteriole and have been shown to accelerate CKD in African Americans with low renal function, but the mechanisms are unknown. We used an established integrative mathematical model of human physiology, HumMod, to create a virtual population of African Americans using clinical data (ALLHAT trial). We tested the hypothesis that DHP CCB therapy exacerbates pressure-induced glomerular injury in hypertensive CKD. After two years of simulating angiotensin converting enzyme (ACE) inhibition or CCB, there were statistically similar blood pressure and glomerular filtration rate (GFR) before and after treatment as compared to African American patients. ACE inhibition decreased blood pressure in the virtual population and was not associated with significant changes in glomerular pressure or injury. However, despite having significant falls in blood pressure, chronic CCB therapy was associated with increases in glomerular pressure and significantly increased glomerular damage. High glomerular injury or pressure and single nephron GFR predicted glomerulosclerosis in these models. The results from these simulations suggest that DHP (L-type) CCBs may potentiate glomerular HTN in at risk African Americans (low renal function) and that efferent arteriolar vasodilation with blockers of the renin-angiotensin system may ameliorate CKD progression. While these simulations and results are clinically relevant, the predictions presented in these simulations are to be considered hypotheses until confirmed with experimental and clinical investigation.

Peng Li

(Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA)
"Resting Heart Rate Complexity and All-Cause and Cardiorespiratory Mortality in a Middle-to-Older Aged, Population Cohort"
Spontaneous heart rate fluctuations contain rich information related to health and illness in terms of physiological complexity, an accepted indicator of plasticity and adaptability. However, it is challenging to make inferences on complexity from shorter, more practical epochs of data. Distribution entropy (DistEn) is a recently introduced complexity measure that is designed specifically for shorter duration heartbeat recordings. We hypothesized that reduced DistEn predicts increased mortality in a large population cohort. The prognostic value of DistEn was examined in 7,631 middle-older aged UK Biobank participants who had 2-minute resting electrocardiograms (ECG) conducted (mean age 59.5 years; 60.4% female). During a median follow-up period of 7.8 years, 451 (5.9%) participants died. In Cox proportional hazards models with adjustment for demographics, lifestyle factors, physical activity, cardiovascular risks, and comorbidities, for each 1 standard deviation decrease in DistEn, the risk increased by 36%, 56% and 73%, for all-cause, cardiovascular and respiratory disease related mortality, respectively. These effect sizes were equivalent to the risk of death from being over 5 years older, having been a former smoker or suffering from diabetes mellitus. Lower DistEn was most predictive of death in those under 55 years with a prior myocardial infarction, representing an additional 56% risk for mortality compared to older subjects without. These observations remained after controlling for traditional mortality predictors, resting heart rate and HRV. Resting heart rate complexity from short, resting ECGs was independently associated with mortality in middle to older aged adults. These risks appear most pronounced in middle-aged subjects with prior MI, and may uniquely contribute to mortality risk screening.

Ashwin Belle

(Fifth Eye Inc., Ann Arbor, MI, USA)
"Hemodynamic Monitoring: Seeing the Unseen"
This talk will discuss the various challenges in cardiac monitoring particularly from a hemodynamic perspective and also discuss some of the current methods and research efforts to predict future cardiovascular events from real-time data. This discussion will be from a commercial prospective of how to plumb the interface between mathematics and diagnostics for better treatment and outcome. A project using real time clinical data to predict future cardiovascular events was developed from a concept at the University of Michigan where sophisticated machine learning was applied to an information-dense ECG signal to predict patient deterioration in the context of hypovolemia. Bringing this research concept to the commercial arena involved developing a data collection framework along with software tools and computational infrastructure. This was the birth of of the company Fifth Eye which brings this technology to the clinic.

Hosted by SMB2021 Follow
Virtual conference of the Society for Mathematical Biology, 2021.